Publications
1. Biase, Maria A Di; Tian, Ye Ella; Bethlehem, Richard A I; Seidlitz, Jakob; Alexander-Bloch, Aaron F; Yeo, B T Thomas; Zalesky, Andrew
Mapping human brain charts cross-sectionally and longitudinally Journal Article
In: Proc. Natl. Acad. Sci. U. S. A., vol. 120, no. 20, pp. e2216798120, 2023.
Abstract | BibTeX | Tags: brain trajectory; cross-sectional; individual prediction; longitudinal; normative models
@article{Di_Biase2023-lg,
title = {Mapping human brain charts cross-sectionally and longitudinally},
author = {Maria A Di Biase and Ye Ella Tian and Richard A I Bethlehem and Jakob Seidlitz and Aaron F Alexander-Bloch and B T Thomas Yeo and Andrew Zalesky},
year = {2023},
date = {2023-05-01},
journal = {Proc. Natl. Acad. Sci. U. S. A.},
volume = {120},
number = {20},
pages = {e2216798120},
abstract = {Brain scans acquired across large, age-diverse cohorts have
facilitated recent progress in establishing normative brain aging
charts. Here, we ask the critical question of whether
cross-sectional estimates of age-related brain trajectories
resemble those directly measured from longitudinal data. We show
that age-related brain changes inferred from cross-sectionally
mapped brain charts can substantially underestimate actual
changes measured longitudinally. We further find that brain aging
trajectories vary markedly between individuals and are difficult
to predict with population-level age trends estimated
cross-sectionally. Prediction errors relate modestly to
neuroimaging confounds and lifestyle factors. Our findings
provide explicit evidence for the importance of longitudinal
measurements in ascertaining brain development and aging
trajectories.},
keywords = {brain trajectory; cross-sectional; individual prediction; longitudinal; normative models},
pubstate = {published},
tppubtype = {article}
}
Brain scans acquired across large, age-diverse cohorts have
facilitated recent progress in establishing normative brain aging
charts. Here, we ask the critical question of whether
cross-sectional estimates of age-related brain trajectories
resemble those directly measured from longitudinal data. We show
that age-related brain changes inferred from cross-sectionally
mapped brain charts can substantially underestimate actual
changes measured longitudinally. We further find that brain aging
trajectories vary markedly between individuals and are difficult
to predict with population-level age trends estimated
cross-sectionally. Prediction errors relate modestly to
neuroimaging confounds and lifestyle factors. Our findings
provide explicit evidence for the importance of longitudinal
measurements in ascertaining brain development and aging
trajectories.